Residents' satisfaction and suggestions to improve nephrology residency in Italy, and comparison with the organization in other European countries.

BACKGROUND: In Italy, nephrology residency is available in twenty-one nephrology schools, each with its own strengths and weaknesses. The present study is aimed at exploring the residents' satisfaction with their training programs. METHODS: Between April 20th and May 19th, 2021, a questionnaire on residency satisfaction consisting of 49 items was sent to 586 residents and 175 recently certified specialists (qualified to practice as nephrologists in 2019 and 2020), with a response rate of 81% and 51%, respectively. The teaching organization was contextualized with a survey involving 13 European nephrology schools. RESULTS: Most residency fellowship programs received a good rating with regard to "satisfaction", in particular for the following items: number of hospitalizations followed-up, chronic hemodialysis training, follow-up of transplanted patients, diagnosis and treatment of glomerulonephritis. The teachings that were identified as being of lower quality or insufficient intensity included vascular access management, ultrasound diagnostics and renal nutrition. The need for improvement in formal teaching programs was underlined. Young nephrologists were rather satisfied with their salary and with the quality of the work they were doing, but only few were interested in an academic career since it was generally held that it is "too difficult" to obtain a university position. Many young nephrologists who filled in the questionnaire felt that lack of experience in peritoneal dialysis and vascular access management was a barrier to finding an ideal job. Compared to other European training programs, the Italian program differs with regard to longer exposure to nephrology (as compared to internal medicine), and greater flexibility for internships in different settings, including abroad. CONCLUSIONS: This first nationwide survey on the satisfaction of residents in nephrology indicates that, despite rather good overall satisfaction, there is room for improvement to make nephrology a more appealing choice and to fulfill the needs of a growing number of renal disease patients.

Spatial mismatch between wild bee diversity hotspots and protected areas.

Wild bees are critical for multiple ecosystem functions but are currently threatened. Understanding the determinants of the spatial distribution of wild bee diversity is a major research gap for their conservation. We modeled wild bee α and ß taxonomic and functional diversity in Switzerland to uncover countrywide diversity patterns and determine the extent to which they provide complementary information, assess the importance of the different drivers structuring wild bee diversity, identify hotspots of wild bee diversity, and determine the overlap between diversity hotspots and the network of protected areas. We used site-level occurrence and trait data from 547 wild bee species across 3343 plots and calculated community attributes, including taxonomic diversity metrics, community mean trait values, and functional diversity metrics. We modeled their distribution with predictors describing gradients of climate, resource availability (vegetation), and anthropogenic influence (i.e., land-use types and beekeeping intensity). Wild bee diversity changed along gradients of climate and resource availability; high-elevation areas had lower functional and taxonomic α diversity, and xeric areas harbored more diverse bee communities. Functional and taxonomic ß diversities diverged from this pattern, with high elevations hosting unique species and trait combinations. The proportion of diversity hotspots included in protected areas depended on the biodiversity facet, but most diversity hotspots occurred in unprotected land. Climate and resource availability gradients drove spatial patterns of wild bee diversity, resulting in lower overall diversity at higher elevations, but simultaneously greater taxonomic and functional uniqueness. This spatial mismatch among distinct biodiversity facets and the degree of overlap with protected areas is a challenge to wild bee conservation, especially in the face of global change, and calls for better integrating unprotected land. The application of spatial predictive models represents a valuable tool to aid the future development of protected areas and achieve wild bee conservation goals.

Desajuste espacial entre los puntos calientes de diversidad de abejas silvestres y las áreas protegidas Resumen Las abejas silvestres son de suma importancia para muchas funciones ecosistémicas, pero hoy en día se encuentran amenazadas. Conservarlas requiere de investigación para entender las determinantes de su distribución espacial. Modelamos la diversidad funcional y taxonómica α y ß de las abejas silvestres en Suiza para revelar los patrones de diversidad en el país y determinar el grado al que proporcionan información complementaria. También analizamos la importancia de los diferentes impulsores que estructuran la diversidad de las abejas silvestres, identificamos puntos calientes para su diversidad y determinamos el traslape entre estos puntos calientes y la red de áreas protegidas. Usamos datos de los rasgos y la existencia a nivel de sitio de 547 especies de abejas silvestres en 3343 parcelas y calculamos los atributos comunitarios, incluyendo las medidas de diversidad taxonómica, los valores medios de las características de la comunidad y las medidas de diversidad funcional. Modelamos la distribución de las especies de abejas con indicadores que describieron las gradientes climáticas, de disponibilidad de recursos (vegetación) y de influencia antropogénica (es decir, tipos de uso de suelo e intensidad de apicultura). La diversidad de abejas silvestres cambió junto con los gradientes climáticos y de disponibilidad de recursos; las áreas elevadas tuvieron una diversidad funcional y taxonómica α más baja y las áreas xerófilas albergaron comunidades de abejas más diversas. Las diversidades funcional y taxonómica ß difirieron de este patrón pues las áreas elevadas albergaron especies y combinaciones de características únicas. La proporción de los puntos calientes de diversidad incluidos en las áreas protegidas dependieron de la faceta de la biodiversidad, aunque la mayoría de los puntos calientes se ubicaron en suelo no protegido. Los gradientes climáticos y de disponibilidad de recursos fueron factores en los patrones espaciales de la diversidad de abejas silvestres, lo que resultó en una diversidad general más baja en las áreas elevadas, pero a la vez con una mayor singularidad taxonómica y funcional. Este desfase espacial entre las diferentes facetas de la biodiversidad y el traslape con las áreas protegidas es un reto para la conservación de las abejas silvestres, especialmente de cara al cambio global, y requiere de una mejor integración del suelo no protegido. La aplicación de los modelos espaciales predictivos es una herramienta importante de apoyo para el desarrollo de áreas protegidas en el futuro y para lograr los objetivos de conservación de las abejas silvestres.

Using leaf traits to explain species co-existence and its consequences for primary productivity across a forest-steppe ecotone.

Trait-based approaches have been widely applied to uncover the mechanisms determining community assembly and biodiversity-ecosystem functioning relationships. However, they have rarely been used in forest-steppe ecotones. These ecosystems are extremely sensitive to disturbances due to their relatively complex ecosystem structures, functionings and processes. In this study, we selected seven sites along a transect from closed canopy forests (CF) to forest-steppe ecotones (FSE) and meadow steppes (MS) in northeast China. Six leaf functional traits (i.e. leaf nitrogen and phosphorus contents, leaf length and thickness, single leaf area and leaf mass per unit area, LMA) as well as the community composition and aboveground biomass at each site were measured. Both functional trait diversity indices (richness, evenness and divergence) and community-weighted mean trait values (CWMs) were calculated to quantify community trait distributions. We found that dominant species in the FSE communities showed acquisitive strategies with highest leaf nitrogen (Mean ± SE: 19.6 ± 0.5 mg g-1) and single leaf area (19.2 ± 1.3 cm2), but the lowest LMA (59.6 ± 1.3 g cm-2) values compared to adjacent CF and MS communities. The ecotone communities also exhibited the largest functional trait richness (TOP), evenness (TED) and divergence (FDis) values (0.46, 0.92 and 0.67, respectively). Overall, niche differentiation emerges as the main mechanism influencing the coexistence of plant species in ecotone ecosystems. In addition, CWMs of leaf traits were the most important predictors for estimating variations in aboveground productivity across the transect, suggesting a major influence of dominant species. Our findings suggest that vegetation management practices in forest-steppe ecotones should increasingly focus on community functional trait diversity, and support the establishment and regeneration of plant species with rapid resource acquisition strategies.

Low resource availability drives feeding niche partitioning between wild bees and honeybees in a European city.

Cities are socioecological systems that filter and select species, therefore establishing unique species assemblages and biotic interactions. Urban ecosystems can host richer wild bee communities than highly intensified agricultural areas, specifically in resource-rich urban green spaces such as allotments and family gardens. At the same time, urban beekeeping has boomed in many European cities, raising concerns that the fast addition of a large number of managed bees could deplete the existing floral resources, triggering competition between wild bees and honeybees. Here, we studied the interplay between resource availability and the number of honeybees at local and landscape scales and how this relationship influences wild bee diversity. We collected wild bees and honeybees in a pollination experiment using four standardized plant species with distinct floral morphologies. We performed the experiment in 23 urban gardens in the city of Zurich (Switzerland), distributed along gradients of urban and local management intensity, and measured functional traits related to resource use. At each site, we quantified the feeding niche partitioning (calculated as the average distance in the multidimensional trait space) between the wild bee community and the honeybee population. Using multilevel structural equation models (SEM), we tested direct and indirect effects of resource availability, urban beekeeping, and wild bees on the community feeding niche partitioning. We found an increase in feeding niche partitioning with increasing wild bee species richness. Moreover, feeding niche partitioning tended to increase in experimental sites with lower resource availability at the landscape scale, which had lower abundances of honeybees. However, beekeeping intensity at the local and landscape scales did not directly influence community feeding niche partitioning or wild bee species richness. In addition, wild bee species richness was positively influenced by local resource availability, whereas local honeybee abundance was positively affected by landscape resource availability. Overall, these results suggest that direct competition for resources was not a main driver of the wild bee community. Due to the key role of resource availability in maintaining a diverse bee community, our study encourages cities to monitor floral resources to better manage urban beekeeping and help support urban pollinators.

An Overview of Sensors for Long Range Missile Defense.

Given the increasing tensions between world powers, missile defense is a topic that is more relevant than ever. However, information on the subject is often fragmented, confusing and untrustworthy. On the other hand, we believe that an informed overview of the current status is important for decision makers and citizens alike. A missile is essentially a guided rocket and therefore the term can be used to describe a very wide range of weapon systems. In this paper, we focus on long-range and intercontinental threats, which we believe are more important and problematic to defend against. We provide an overview of the two most common types of sensors, space-based infrared sensors and radars, and highlight their peculiarities and, most importantly, their drawbacks that severely limit their effectiveness.

GTASynth: 3D synthetic data of outdoor non-urban environments.

Developing point clouds registration, SLAM or place recognition algorithms requires data with a high quality ground truth (usually composed of a position and orientation). Moreover, many machine learning algorithms require large amounts of data for training. However, acquiring this kind of data in non-urban outdoor environments poses several challenges. First of all, off-road robots are usually very expensive. Above all, producing an accurate ground truth is problematic. Even the best sensor available, i.e. RTK GPS, cannot guarantee the required accuracy in every condition. Hence the scarcity of this kind of dataset for point clouds registration or SLAM in off-road conditions. For these reasons, we propose a synthetic dataset generated using Grand Theft Auto V (GTAV), a video game that accurately simulates sensing in outdoor environments. The data production technique is based on DeepGTAV-PreSIL [1]: a simulated LiDAR and a camera are installed on a vehicle which is driven through the GTAV map. Since one of the goals of our work is to produce a large amount of data to train neural networks which will then be used with real data, we have chosen the characteristics of the sensors to accurately simulate real ones. The proposed dataset is composed of 16.207 point clouds and images, divided into five sequences representing different environments, such as fields, woods and mountains. For each pair of point clouds and images we also provide the ground truth pose of the vehicle at the acquisition.

[The FRASNET study: identification of clinical and social factors of renal failure in an elderly population].

Background. Chronic renal failure is an epidemic in elderly patients. Older population have an increased prevalence of frailty and sarcopenia, associated with a wide range of adverse health outcomes such as falls, hospitalization, disability. Aim. Describe the sociodemographic and clinical variables of an elderly Lombard population and identify predictors of renal insufficiency. Materials and methods. Cross-sectional observational study conducted in hospitals, in recreational centers for the elderly, in the Universities of the Third Age of the provinces of Milan and Monza-Brianza conducted through a convenience sampling of 1250 subjects over the age of 65. Results. The study identified living alone, annual individual income < € 10,000, polypharmacy, sarcopenia and frailty as predictors of chronic kidney failure. The sample has a mean eGFR of 71.74 mL/min/1.73m2 (SD ± 16.56). Older people living alone are more likely to develop CRI (P = 0.031, confidence interval, CI [1.031-1.905]) as well as having an income < € 10,000 (P = 0.002, CI [0.392-0.923]). Taking more than 11 drugs a day increases the probability of having chronic renal failure by 16 times (P = 0.012, CI [1.155-3.16]). Sarcopenia and frailty increase the likelihood of having chronic renal failure (CRI) (P = 0.001, CI [1.198-2.095]). Conclusions. Identifying predictors of chronic kidney failure is a key step in introducing preventive measures and providing better care to the elderly population.

The Influence of Fine-Scale Grazing Heterogeneity on Dung Beetle Assemblages: What Trait Analysis Teaches Us.

Livestock grazing puts major anthropogenic pressure on biological communities worldwide. Not all species are expected to be affected in the same way, and the impacts will depend on species' traits. Focusing on traits thus helps identify the mechanisms underlying changes in community composition under grazing pressures. We investigated how fine-scale grazing heterogeneity affects the trait composition and diversity of dung beetle assemblages in Western Europe. We sampled dung beetles in habitat patches differing in terms of grazing intensity within rangelands of two distinct biogeographical areas: a Mediterranean lowland steppe and Western alpine meadows. We measured five morphological traits expected to respond to the local-scale filtering pressure exerted by variations in grazing intensity. Using individual-based data, we assessed responses in terms of single-trait mean values in communities and complementary trait diversity indices. We found strong shifts in trait composition and diversity between the habitat patches. In both study areas, variations in habitat conditions are likely to have filtered the local occurrence and abundance of dung beetles by the mean of traits such as body mass (which have several functional implications), as well as traits linked to underground activity. We hypothesize that fine-scale variation in resource availability (i.e., droppings) and disturbance intensity (i.e., trampling) are key drivers of the observed patterns in species assemblages. Trait richness peaks at moderate grazing intensity in both study areas, suggesting that patches with an intermediated level of available resources and soil disturbance enable individuals with a greater range of autecological requirements to coexist.

Reproductive trait differences drive offspring production in urban cavity-nesting bees and wasps.

The contrasting and idiosyncratic changes in biodiversity that have been documented across urbanization gradients call for a more mechanistic understanding of urban community assembly. The reproductive success of organisms in cities should underpin their population persistence and the maintenance of biodiversity in urban landscapes. We propose that exploring individual-level reproductive traits and environmental drivers of reproductive success could provide the necessary links between environmental conditions, offspring production, and biodiversity in urban areas. For 3 years, we studied cavity-nesting solitary bees and wasps in four urban green space types across Toronto, Canada. We measured three reproductive traits of each nest: the total number of brood cells, the proportion of parasite-free cells, and the proportion of non-emerged brood cells that were parasite-free. We determined (a) how reproductive traits, trait diversity and offspring production respond to multiple environmental variables and (b) how well reproductive trait variation explains the offspring production of single nests, by reflecting the different ways organisms navigate trade-offs between gathering of resources and exposure to parasites. Our results showed that environmental variables were poor predictors of mean reproductive trait values, trait diversity, and offspring production. However, offspring production was highly positively correlated with reproductive trait evenness and negatively correlated with trait richness and divergence. This suggests that a narrow range of reproductive traits are optimal for reproduction, and the even distribution of individual reproductive traits across those optimal phenotypes is consistent with the idea that selection could favor diverse reproductive strategies to reduce competition. This study is novel in its exploration of individual-level reproductive traits and its consideration of multiple axes of urbanization. Reproductive trait variation did not follow previously reported biodiversity-urbanization patterns; the insensitivity to urbanization gradients raise questions about the role of the spatial mosaic of habitats in cities and the disconnections between different metrics of biodiversity.

Vehicle Localization Using 3D Building Models and Point Cloud Matching.

Detecting buildings in the surroundings of an urban vehicle and matching them to building models available on map services is an emerging trend in robotics localization for urban vehicles. In this paper, we present a novel technique, which improves a previous work by detecting building façade, their positions, and finding the correspondences with their 3D models, available in OpenStreetMap. The proposed technique uses segmented point clouds produced using stereo images, processed by a convolutional neural network. The point clouds of the façades are then matched against a reference point cloud, produced extruding the buildings' outlines, which are available on OpenStreetMap (OSM). In order to produce a lane-level localization of the vehicle, the resulting information is then fed into our probabilistic framework, called Road Layout Estimation (RLE). We prove the effectiveness of this proposal, testing it on sequences from the well-known KITTI dataset and comparing the results concerning a basic RLE version without the proposed pipeline.

Reconciling trait based perspectives along a trait-integration continuum.

Trait based ecology has developed fast in the last decades, aiming to both explain mechanisms of community assembly, and predict patterns in nature, such as the effects of biodiversity shifts on key ecosystem processes. This body of work has stimulated the development of several conceptual frameworks and analytical methods, as well as the production of trait databases covering a growing number of taxa and organizational levels (from individuals to guilds). However, this breeding ground of novel concepts and tools currently lacks a general and coherent framework, under which functional traits can help ecologists organize their research aims, and serve as the common currency to unify several scientific disciplines. Specifically, we see a need to bridge the gaps between community ecology, ecosystem ecology, and evolutionary biology, in order to address the most pressing environmental issues of our time. To achieve this integration goal, we define a trait-integration continuum, which reconciles alternative trait definitions and approaches in ecology. This continuum outlines a coherent progression of biological scales, along which traits interact and hierarchically integrate from genetic information, to whole organism fitness-related traits, to trait syndromes and functional groups. Our conceptual scheme proposes that lower-level trait integration is closer to the inference of ecoevolutionary mechanisms determining population and community properties, whereas higher-level trait integration is most suited to the prediction of ecosystem processes. Within these two extremes, trait integration varies on a continuous scale, which relates directly to the inductive-deductive loop that should characterize the scientific method. With our proposed framework, we aim to facilitate scientists in contextualising their research based on the trait-integration levels that matter most to their specific goals. Explicitly acknowledging the existence of a trait-integration continuum is a promising way for framing the appropriate questions, thus obtaining reliable answers and results that are comparable across studies and disciplines.

Klotho Gene in Human Salt-Sensitive Hypertension.

BACKGROUND AND OBJECTIVES: Hypertension is a common aging-related disorder. Salt intake is one of the main environmental factors contributing to the development of hypertension. Transgenic mice with one-half Klotho deficiency displayed a spontaneous BP increase and salt-sensitive hypertension in response to high sodium intake. Usually circulating levels of α-Klotho decrease with age, and this reduction may be stronger in patients with several aging-related diseases. This study aimed at exploring the association of Klotho with salt sensitivity in humans. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The role of Klotho polymorphisms and α-Klotho serum levels was evaluated in patients with hypertension who were treatment naive and underwent an acute salt-sensitivity test (discovery n=673, intravenous 2 L of 0.9% saline in 2 hours). Salt sensitivity was defined as a mean BP increase of >4 mm Hg at the end of the infusion. A total of 32 single nucleotide polymorphisms in the Klotho gene (KL), previously identified with a genome-wide association study, were used in the genetic analysis and studied for a pressure-natriuresis relationship. RESULTS: Of the patients with hypertension, 35% were classified as salt sensitive. The most relevant polymorphism associated with pressure natriuresis was the common missense single nucleotide polymorphism rs9536314, and the GG and GT genotypes were more represented among patients who were salt sensitive (P=0.001). Those carrying the G allele showed a less steep pressure-natriuresis relationship, meaning that a significant increase in mean BP was needed to excrete the same quantity of salt compared with patients who were salt resistant. KL rs9536314 also replicated the pressure-natriuresis association in an independent replication cohort (n=193) and in the combined analysis (n=866). There was an inverse relationship between circulating Klotho and mean BP changes after the saline infusion (r=-0.14, P=0.03). Moreover, circulating α-Klotho was directly related to kidney function at baseline eGFR (r=0.22, P<0.001). CONCLUSIONS: KL rs9536314 is associated with salt-sensitive hypertension in patients with hypertension who are treatment naive. Moreover, circulating α-Klotho levels were mainly related to diastolic BP changes at the end of a salt load and to eGFR as an expression of kidney aging.

Hypertension in High School Students: Genetic and Environmental Factors: The HYGEF Study.

Hypertension and obesity in the young population are major risk factors for renal and cardiovascular events, which could arise in adulthood. A candidate-gene approach was applied in a cohort observational study, in which we collected data from 2638 high school adolescent students. Participants underwent anthropometric and blood pressure (BP) measurements, as well as saliva and urine sample collection for genomic DNA extraction and renal function evaluation, respectively. We tested whether candidate genes previously implicated in salt-sensitive hypertension in adults impact BP also among adolescents. Since inflammatory mechanisms may be involved in pathophysiology of hypertension and in endothelial dysfunction and atherosclerosis through reactive oxygen species, the baseline urinary excretion of inflammatory and oxidative stress markers in a subgroup of adolescents stratified according to ADD1(alpha adducin) rs4961 genotypes was assessed. Regression analysis of BP values with genetic polymorphisms, highlighted an association with a missense variant of LSS (lanosterol synthase, rs2254524), a gene coding for an enzyme involved in endogenous ouabain synthesis. Higher diastolic and systolic BP were associated with LSS A allele (P=0.011 and P=0.023, respectively). BP resulted associated with 5 more SNPs. The KL (klotho) rs9536314 missense variant was associated with 24 hour urinary Na+ excretion (P=0.0083). Urinary protein tests showed a greater excretion of IL1ß (interleukin 1ß) and interleukin 10 (P<0.0001) in carriers of the ADD1 rs4961 T allele. In conclusion, 3 missense gene variants already implicated in adult hypertension impact BP or Na+ excretion among adolescents, and, together with activated pro-inflammatory pathways, might predispose to early cardiovascular damage.

Urban bumblebees are smaller and more phenotypically diverse than their rural counterparts.

With urbanization identified as being one of the key drivers of change in global land use, and the rapid expansion of urban areas world-wide, it is relevant to evaluate how novel ecological conditions in cities shape species functional traits, which are essential for how species interact with their environments and with each other. Despite the many comparative studies on organisms living in urban and non-urban areas, our knowledge on species responses to urban environments remains limited. For one, much of the ecological research has assumed that the environment changes in a linear fashion from the city core to the city edges, whereas in reality the environments within the cities are highly heterogeneous. Furthermore, studies on species responses to these highly variable ecosystems are often based on interspecific mean trait values, which ignore the potential for high levels of intraspecific variation among individuals in key functional traits. The current study investigated intraspecific functional trait differences for four functional traits associated with body size, mobility and resource selection among rural and urban populations of two common bumblebee species, Bombus pascuorum and Bombus lapidarius, in urban centres and adjacent rural areas in Switzerland. We document shifts in functional traits towards smaller individuals and higher multidimensional trait variation in urban populations compared to rural conspecifics of both species. This shows that urban individuals for both species are on average smaller sized but populations are distinctively different from rural population by increasing their trait richness and diversifying their trait combinations. In addition, we found bimodality in tongue length within urban B. pascuorum populations. Our results suggest that urban and rural populations possibly experience differential selection pressures resulting in trait differences across and among populations. We argue that variations in the respective foraging landscapes in cities leads to smaller sized but phenotypically more diverse populations, and drive functional trait divergence.

The application of a multi-reference control strategy to noise cancelling headphones.

Active noise cancelling (ANC) headphones have seen significant commercial success and a number of control strategies have been proposed, including feedforward, feedback, and hybrid configurations, using both analogue and digital implementations. Irrespective of the configuration or implementation approach, the strategies proposed in the open-literature have focused on implementations where the control system for each ear of the headphones operates independently. In this paper, a multi-reference ANC strategy is proposed and investigated for noise cancelling headphones. As with standard feedforward ANC headphones, the system utilises a single error microphone and single reference microphone on each cup; however, in the proposed configuration, the left and right reference microphones are used to achieve control at both the left and right ear cups. The performance of this controller design is compared to a standard single reference feedforward controller implementation under a variety of different sound field conditions. Although the proposed strategy requires an increased computational demand, it is shown that there is a significant control advantage for noise sources originating from the side of the user, whilst the performance for front and rear sources is maintained.

Light limitation increases multidimensional trait evenness in phytoplankton populations.

Individual-level variation arising from responses to environmental gradients influences population and community dynamics. How such responses empirically relate to the mechanisms that govern species coexistence is, however, poorly understood. Previous results from l ake phytoplankton communities suggested that the evenness of organismal traits in multiple dimensions increases with resource limitation, possibly due to resource partitioning at the individual level. Here we experimentally tested the emergence of this pattern by growing two phytoplankton species (Pseudokirchneriella subcapitata and Microcystis aeruginosa) under a gradient of light intensity, in monoculture and jointly. Under low light (resource) conditions, the populations diversified into a wide range of phenotypes, which were evenly distributed in multidimensional trait space (defined by four pigment-related trait dimensions), consistent with the observed field pattern. Our interpretation is that under conditions of light limitation, individual phytoplankton cells alter photosynthetic traits to reduce overlap in light acquisition, acquiring unexploited resources and thereby likely maximising individual success. Our results provide prime experimental evidence that resource limitation increases the evenness of conspecific and heterospecific microbial phenotypes along trait axes, advancing our understanding of trait-based coexistence.

Lanosterol Synthase Genetic Variants, Endogenous Ouabain, and Both Acute and Chronic Kidney Injury.

RATIONALE & OBJECTIVE: Studies of humans and animals have suggested that endogenous ouabain (EO) and related genes are mediators of acute (AKI) and chronic kidney injury. We sought to examine the relationship among EO levels, genetic variants in lanosterol synthase (LSS; an enzyme that catalyzes synthesis of cholesterol, a precursor of EO), and both AKI and chronic kidney injury. STUDY DESIGN: 2 prospective observational cohort studies and a cross-sectional study of kidney tissue. SETTING & PARTICIPANTS: (1) A prospective cohort study of patients undergoing cardiovascular surgery, (2) measurement of EO concentration in kidney tissue removed because of an adjacent tumor, and (3) a prospective cohort study of patients with newly diagnosed essential hypertension. EXPOSURE: Missense variant in LSS (A instead of C allele at rs2254524), which leads to a valine to leucine substitution at amino acid 642. OUTCOMES: Development of postoperative AKI in the cardiovascular surgery cohort, EO concentration in kidney tissue, and estimated glomerular filtration rate (eGFR) reductions in the essential hypertension cohort. ANALYTICAL APPROACH: Logistic regression for analysis of postoperative AKI, analysis of variance for EO concentration in kidney tissue, and generalized linear models for changes in eGFR over time. RESULTS: AKI incidence following cardiovascular surgery was greater among those with the LSS rs2254524 AA genotype (30.7%) than in those with the CC genotype (17.4%; P=0.001). LSS rs2254524 AA kidneys had higher EO concentrations than CC kidneys (2.14±0.29 vs 1.25±0.08ng/g; P<0.001). In the longitudinal study of patients with essential hypertension (median follow-up, 4 years; range, 1-15 years), eGFR decline was greater among the LSS rs2254524 AA genotype group (-4.39±1.18mL/min/1.73m2 per year) than in the AC or CC genotype groups (-1.07±0.55 and -2.00±0.45mL/min/1.73m2 per year respectively; P = 0.03). LIMITATIONS: These associations do not necessarily represent causal relationships; LSS rs2254524 variants may have effects on other steroid hormones. CONCLUSIONS: These findings support the potential value of LSS rs2254524 genotype-based risk stratification to identify patients at high risk for AKI before cardiovascular surgery, as well as predict accelerated eGFR in the setting of hypertension. These findings also suggest that LSS may in part drive EO-mediated kidney damage. EO may represent a new potential therapeutic target for the prevention of AKI and slowing of kidney damage in the setting of hypertension.

Diversity in form and function: Vertical distribution of soil fauna mediates multidimensional trait variation.

It has been widely recognized that species show extensive variation in form and function. Based on species' attributes, they can be positioned along major axes of variation, which are often defined by life-history traits, such as number of offspring, age at maturity or generation time. Less emphasis has been given in this respect to tolerance traits, especially to resistance to abiotic stress conditions, which often determine community (dis)assembly and distribution. Soil fauna species distribution is governed to a large extent by environmental conditions that filter communities according to functional traits, such as abiotic stress tolerance, morphology and body size. Trait-based approaches have been successfully used to predict soil biota responses to abiotic stress. It remains unclear, though, how these traits relate to life-history traits that determine individual performance, that is, reproduction and survival. Here, we analyse patterns in multidimensional trait distribution of dominant groups of soil fauna, that is, Isopoda, Gastropoda and Collembola, known to be important to the functioning of ecosystems. We compiled trait information from existing literature, trait databases and supplementary measurements. We looked for common patterns in major axes of trait variation and tested if vertical distribution of species in the soil explained trait variation based on three components of trait diversity (trait richness, evenness and divergence). Our results showed that two to three axes of variation structured the trait space of life-history and tolerance traits in each of the taxonomic groups and that vertical distribution in soil explained the main axis of trait variation. We also found evidence of environmental filtering on soil fauna along the vertical soil distribution, with lower trait richness and trait divergence in soil-dwelling than in surface-living species. Our study was partially limited by the lack of detailed trait measurements for the selected taxonomic groups. In this regard, there is an urgent need for standardized trait databases across invertebrate groups to improve trait-based diversity analysis and fill gaps in the mechanistic understanding behind trait distribution, trait filtering and the link with species fitness and performance.

Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering.

Scanning flow cytometry (SFCM) is characterized by the measurement of time-resolved pulses of fluorescence and scattering, enabling the high-throughput quantification of phytoplankton morphology and pigmentation. Quantifying variation at the single cell and colony level improves our ability to understand dynamics in natural communities. Automated high-frequency monitoring of these communities is presently limited by the absence of repeatable, rapid protocols to analyse SFCM datasets, where images of individual particles are not available. Here we demonstrate a repeatable, semi-automated method to (1) rapidly clean SFCM data from a phytoplankton community by removing signals that do not belong to live phytoplankton cells, (2) classify individual cells into trait clusters that correspond to functional groups, and (3) quantify the biovolumes of individual cells, the total biovolume of the whole community and the total biovolumes of the major functional groups. Our method involves the development of training datasets using lab cultures, the use of an unsupervised clustering algorithm to identify trait clusters, and machine learning tools (random forests) to (1) evaluate variable importance, (2) classify data points, and (3) estimate biovolumes of individual cells. We provide example datasets and R code for our analytical approach that can be adapted for analysis of datasets from other flow cytometers or scanning flow cytometers.

The predictability of a lake phytoplankton community, over time-scales of hours to years.

Forecasting changes to ecological communities is one of the central challenges in ecology. However, nonlinear dependencies, biotic interactions and data limitations have limited our ability to assess how predictable communities are. Here, we used a machine learning approach and environmental monitoring data (biological, physical and chemical) to assess the predictability of phytoplankton cell density in one lake across an unprecedented range of time-scales. Communities were highly predictable over hours to months: model R2 decreased from 0.89 at 4 hours to 0.74 at 1 month, and in a long-term dataset lacking fine spatial resolution, from 0.46 at 1 month to 0.32 at 10 years. When cyanobacterial and eukaryotic algal cell densities were examined separately, model-inferred environmental growth dependencies matched laboratory studies, and suggested novel trade-offs governing their competition. High-frequency monitoring and machine learning can set prediction targets for process-based models and help elucidate the mechanisms underlying ecological dynamics.